Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Haijia Wen"'
Publikováno v:
Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 3, Pp 508-523 (2024)
For landslide prevention and control, it is essential to establish a landslide susceptibility prediction framework that can explain the model’s decision-making process. Wushan County, Chongqing was selected as the study area, and seventeen landslid
Externí odkaz:
https://doaj.org/article/6fe082c8f95b4516aa63c9a572921712
Publikováno v:
Resilient Cities and Structures, Vol 3, Iss 4, Pp 34-51 (2024)
Natural and human-made disasters are threatening cities around the world. The resilience of cities plays a critical role in disaster risk response and post-disaster recovery. In mountainous cities, landslides are among the most frequent and destructi
Externí odkaz:
https://doaj.org/article/d3d518d05b7b48559c26e97e179161e0
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 8, Pp 3221-3232 (2024)
Boosting algorithms have been widely utilized in the development of landslide susceptibility mapping (LSM) studies. However, these algorithms possess distinct computational strategies and hyperparameters, making it challenging to propose an ideal LSM
Externí odkaz:
https://doaj.org/article/6029f72b38414ba7887c01b27b78457c
Autor:
Youchen Zhu, Deliang Sun, Haijia Wen, Qiang Zhang, Qin Ji, Changming Li, Pinggen Zhou, Jianjun Zhao
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 15, Iss 1 (2024)
Crafting landslide susceptibility mapping is pivotal for the effective management of landslide risks. However, the influence of non-landslide sample selection on the modeling performance of landslide susceptibility assessment models remains a crucial
Externí odkaz:
https://doaj.org/article/eccbdd4649844af9b29dbaa0562b98ab
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 15, Iss 1 (2024)
Automatic detection of the heavy rainfall-induced landslide clusters based on optical remote sensing images had low accuracy due to the interference of many features. This work proposes a method to improve the accuracy of landslide identification bas
Externí odkaz:
https://doaj.org/article/4f81109285354b44af1079181ce9cf21
A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)
AbstractThe quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct a data-driven landslide susceptibility model that takes into account the selection of non-landslide samples. First,
Externí odkaz:
https://doaj.org/article/bb016fa7dd7a4069a7721e0d6e5572d4
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)
AbstractLandslides have differential characteristics in different regions. This study explores landslide susceptibility mapping (LSM) based on different evaluation units and proposes a strategy for landslides’ differential characteristics in differ
Externí odkaz:
https://doaj.org/article/8a392b313e1942b2a1f97cfd2bd82b19
Publikováno v:
Land, Vol 12, Iss 5, p 1018 (2023)
(1) Background: The aim of this paper was to study landslide susceptibility mapping based on interpretable machine learning from the perspective of topography differentiation. (2) Methods: This paper selects three counties (Chengkou, Wushan and Wuxi
Externí odkaz:
https://doaj.org/article/18cab6d401a04c259eee791ef0b9794d
Publikováno v:
Remote Sensing, Vol 15, Iss 9, p 2226 (2023)
This study aims to develop different-classification-scheme-based building-seismic-resilience (BSR)-mapping models using random forest (RF) and a support vector machine (SVM). Based on a field survey of earthquake-damaged buildings in Shuanghe Town, t
Externí odkaz:
https://doaj.org/article/694dd24b64de44af893c4d2eb223116c
Publikováno v:
Geofluids, Vol 2022 (2022)
A reasonable support scheme is the main factor to be considered when constructing tunnels, and it is essential to accurately calculate the surrounding rock pressure of tunnels. This work focuses on the improved method used to calculate the surroundin
Externí odkaz:
https://doaj.org/article/ad1c2d6b151b453189e7e2a8047b1ddd